def test_1(self):
x, y, z = map(MyVariable, 'xyz')
e = op3(op4(x, y))
g = FunctionGraph([x, y, z], [e])
# print g
opt = EquilibriumOptimizer(
[PatternSub((op1, 'x', 'y'), (op2, 'x', 'y')),
PatternSub((op4, 'x', 'y'), (op1, 'x', 'y')),
PatternSub((op3, (op2, 'x', 'y')), (op4, 'x', 'y'))
],
max_use_ratio=10)
opt.optimize(g)
# print g
assert str(g) == '[Op2(x, y)]'
def test_1(self):
x, y, z = map(MyVariable, 'xyz')
e = op3(op4(x, y))
g = FunctionGraph([x, y, z], [e])
# print g
opt = EquilibriumOptimizer([
PatternSub((op1, 'x', 'y'), (op2, 'x', 'y')),
PatternSub((op4, 'x', 'y'), (op1, 'x', 'y')),
PatternSub((op3, (op2, 'x', 'y')), (op4, 'x', 'y'))
],
max_use_ratio=10)
opt.optimize(g)
# print g
assert str(g) == '[Op2(x, y)]'
def test_1(self):
x, y, z = map(MyVariable, "xyz")
e = op3(op4(x, y))
g = FunctionGraph([x, y, z], [e])
# print g
opt = EquilibriumOptimizer(
[
PatternSub((op1, "x", "y"), (op2, "x", "y")),
PatternSub((op4, "x", "y"), (op1, "x", "y")),
PatternSub((op3, (op2, "x", "y")), (op4, "x", "y")),
],
max_use_ratio=10,
)
opt.optimize(g)
# print g
assert str(g) == "FunctionGraph(Op2(x, y))"
def test_low_use_ratio(self):
x, y, z = map(MyVariable, 'xyz')
e = op3(op4(x, y))
g = FunctionGraph([x, y, z], [e])
# print 'before', g
# display pesky warnings along with stdout
# also silence logger for 'theano.gof.opt'
_logger = logging.getLogger('theano.gof.opt')
oldlevel = _logger.level
_logger.setLevel(logging.CRITICAL)
try:
opt = EquilibriumOptimizer(
[PatternSub((op1, 'x', 'y'), (op2, 'x', 'y')),
PatternSub((op4, 'x', 'y'), (op1, 'x', 'y')),
PatternSub((op3, (op2, 'x', 'y')), (op4, 'x', 'y'))
],
max_use_ratio=1. / len(g.apply_nodes)) # each opt can only be applied once
opt.optimize(g)
finally:
_logger.setLevel(oldlevel)
# print 'after', g
assert str(g) == '[Op1(x, y)]'
def test_low_use_ratio(self):
x, y, z = map(MyVariable, "xyz")
e = op3(op4(x, y))
g = FunctionGraph([x, y, z], [e])
# print 'before', g
# display pesky warnings along with stdout
# also silence logger for 'theano.gof.opt'
_logger = logging.getLogger("theano.gof.opt")
oldlevel = _logger.level
_logger.setLevel(logging.CRITICAL)
try:
opt = EquilibriumOptimizer(
[
PatternSub((op1, "x", "y"), (op2, "x", "y")),
PatternSub((op4, "x", "y"), (op1, "x", "y")),
PatternSub((op3, (op2, "x", "y")), (op4, "x", "y")),
],
max_use_ratio=1.0 / len(g.apply_nodes),
) # each opt can only be applied once
opt.optimize(g)
finally:
_logger.setLevel(oldlevel)
# print 'after', g
assert str(g) == "FunctionGraph(Op1(x, y))"
